Precise indoor localization and tracking of electronic devices

ABSTRACT

Methods and devices useful in performing precise indoor localization and tracking are provided. By way of example, a method includes locating and tracking, via a first wireless electronic device, a plurality of other wireless electronic devices within an indoor environment. The method also includes performing front-back detection, performing stationary node detection, performing angle of arrival (AoA) error correction, and performing field of view (FOV) filtering. Performing indoor localization and tracking of the plurality of other wireless electronic devices includes providing an indication of a physical location of the plurality of other wireless electronic devices within the indoor environment.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a Divisional of and claims priority to U.S.application Ser. No. 15/619,171, entitled “Precise Indoor Localizationand Tracking of Electronic Devices”, filed Jun. 9, 2017, which is aNon-Provisional Patent Application of and claims priority to U.S.Provisional Patent Application No. 62/399,145, entitled “Precise IndoorLocalization and Tracking of Electronic Devices”, filed Sep. 23, 2016,both of which are herein incorporated by reference in their entiretiesand for all purposes.

BACKGROUND

The present disclosure relates generally to wireless electronic devicesand, more particularly, to precise indoor localization and tracking ofwireless electronic devices.

This section is intended to introduce the reader to various aspects ofart that may be related to various aspects of the present disclosure,which are described and/or claimed below. This discussion is believed tobe helpful in providing the reader with background information tofacilitate a better understanding of the various aspects of the presentdisclosure. Accordingly, it should be understood that these statementsare to be read in this light, and not as admissions of prior art.

Transmitters and receivers, or when coupled together as part of a singleunit, transceivers, are commonly included in various electronic devices,and particularly, mobile electronic devices such as, for example, phones(e.g., mobile and cellular phones, cordless phones, personal assistancedevices), computers (e.g., laptops, tablet computers), internetconnectivity routers (e.g., Wi-Fi routers or modems), radios,televisions, wearable electronic devices (e.g., smartwatches, heartratemonitors, exercise wristbands) or any of various other stationary orhandheld devices. Certain types of transceivers, known as wirelesstransceivers, may be used to generate and receive wireless signals to betransmitted and/or received by way of an antenna coupled to thetransceiver. Specifically, the wireless transceiver is generally used toallow the mobile electronic devices to wirelessly communicate data overa network channel or other medium (e.g., air) to and from one or moreexternal mobile electronic devices or other wireless electronic devices.

Indeed, as the worldwide usage of mobile and wearable electronic devices(e.g., mobile phones, tablet computers, smartwatches, and so forth) andin-home wireless electronic devices increases, so has the demand forlocation-based services using the mobile and wearable electronic devicesand in-home wireless electronic devices. For example, in outsideenvironments (e.g., outdoor environments), mobile and wearableelectronic devices may employ global positioning systems (GPS) systemsto provide location and navigation data wherever an unobstructed line ofsight (LoS) channel is available between a number of GPS spacesatellites and the mobile and wearable electronic devices. Yet due tothe requirement of the unobstructed LoS channels between GPS spacesatellites and the mobile and wearable electronic devices, GPS cannotprovide accurate location and navigation data for indoor environments(e.g., inside of residential, commercial, or industrial buildings), andparticularly not for distances less than 2 meters (m). Thus, a number ofindoor positioning systems (IPS) have been developed in an attempt toprovide at least approximate indoor localization and navigation.

For example, one such preeminent example of an IPS system may include a“fingerprinting” system, which may include a technique of developing aradio frequency (RF) map of particular areas of a location orenvironment based on predetermined received signal strength indicators(RSSI) values emanating, for example, from a Wi-Fi connected device orother wireless connectivity “hotspots.” However, “fingerprinting”systems most often includes an offline calibration or training phase inwhich RSSI values must be collected for hundreds if not thousands ofWi-Fi connected devices or other wireless connectivity “hotspots” toachieve even marginal localization accuracy. Furthermore, certainreal-time environmental conditions such as, for example, obstructionsdue to the presence of pedestrians, the opening and closing of doors, aswell as variations in atmospheric conditions (e.g., humidity,temperature) may alter the RF signals and the resulting RSSI values.Moreover, the transceivers employed in many mobile and wearableelectronic devices, as well as those in in-home electronic devices, maybe subject to “front-back” ambiguity, or ambiguity with respect to aparticular wireless electronic device determining whether a signalarrives at that particular wireless electronic device from the front orfrom the back of that particular wireless electronic device.Accordingly, it may be useful to provide methods and devices to improveindoor localization and tracking of wireless electronic devices.

SUMMARY

A summary of certain embodiments disclosed herein is set forth below. Itshould be understood that these aspects are presented merely to providethe reader with a brief summary of these certain embodiments and thatthese aspects are not intended to limit the scope of this disclosure.Indeed, this disclosure may encompass a variety of aspects that may notbe set forth below.

Various embodiments of the present disclosure may be useful inperforming precise indoor localization and tracking of electronicdevices. By way of example, a method includes locating and tracking, viaa first wireless electronic device, a plurality of other wirelesselectronic devices within an indoor environment. The method alsoincludes performing front-back detection, performing stationary nodedetection, performing angle of arrival (AoA) error correction, andperforming field of view (FOV) filtering. Performing indoor localizationand tracking of the plurality of other wireless electronic devicesincludes providing an indication of a physical location of the pluralityof other wireless electronic devices within the indoor environment.

Various refinements of the features noted above may exist in relation tovarious aspects of the present disclosure. Further features may also beincorporated in these various aspects as well. These refinements andadditional features may exist individually or in any combination. Forinstance, various features discussed below in relation to one or more ofthe illustrated embodiments may be incorporated into any of theabove-described aspects of the present disclosure alone or in anycombination. The brief summary presented above is intended only tofamiliarize the reader with certain aspects and contexts of embodimentsof the present disclosure without limitation to the claimed subjectmatter.

BRIEF DESCRIPTION OF THE DRAWINGS

Various aspects of this disclosure may be better understood upon readingthe following detailed description and upon reference to the drawings inwhich:

FIG. 1 is a schematic block diagram of an electronic device including atransceiver, in accordance with an embodiment;

FIG. 2 is a perspective view of a notebook computer representing anembodiment of the electronic device of FIG. 1;

FIG. 3 is a front view of a hand-held device representing anotherembodiment of the electronic device of FIG. 1;

FIG. 4 is a front view of another hand-held device representing anotherembodiment of the electronic device of FIG. 1;

FIG. 5 is a front view of a desktop computer representing anotherembodiment of the electronic device of FIG. 1;

FIG. 6 is a front view and side view of a wearable electronic devicerepresenting another embodiment of the electronic device of FIG. 1;

FIG. 7 is a schematic diagram of the transceiver included within theelectronic device of FIG. 1, in accordance with an embodiment;

FIG. 8 is an example diagram of a radio frequency (RF) map, inaccordance with an embodiment;

FIG. 9 is an example diagram of an RF map illustrating front-backambiguity, in accordance with an embodiment;

FIG. 10 is a flow diagram illustrating an embodiment of a process usefulin correcting front-back ambiguity as part of an indoor localization andtracking technique, in accordance with an embodiment;

FIG. 11 is a flow diagram illustrating an embodiment of a process usefulin identifying flipped nodes as part of an indoor localization andtracking technique, in accordance with an embodiment;

FIG. 12 illustrates an example of front-back signal detection based on adistance calculation, in accordance with an embodiment;

FIG. 13 illustrates an example of front-back signal detection based onan acceleration calculation, in accordance with an embodiment;

FIG. 14 illustrates a table corresponding to the acceleration basedfront-back signal detection of FIG. 13, in accordance with anembodiment;

FIG. 15 is an example diagram of an RF map illustrating an RF map shapeto correct for front-back ambiguity, in accordance with an embodiment;

FIG. 16 is an example diagram of an RF map illustrating an RF map shapeto correct front-back ambiguity, in accordance with an embodiment;

FIG. 17 is an example diagram of another RF map illustrating an RF mapshape with corrected front-back ambiguity, in accordance with anembodiment;

FIG. 18 is an example diagram of another RF map illustrating an RF mapshape with corrected front-back ambiguity, in accordance with anembodiment;

FIG. 19 is a flow diagram illustrating an embodiment of a process usefulin correcting front-back ambiguity as part of an indoor localization andtracking technique, in accordance with an embodiment;

FIG. 20 is an example diagram of RF map illustrating field-of-view (FOV)filtering, in accordance with an embodiment;

FIG. 21 is plot diagram illustrating field-of-view (FOV) filtering, inaccordance with an embodiment; and

FIG. 22 is a flow diagram illustrating an embodiment of a process usefulin performing precise indoor localization and tracking, in accordancewith an embodiment.

DETAILED DESCRIPTION

One or more specific embodiments of the present disclosure will bedescribed below. These described embodiments are only examples of thepresently disclosed techniques. Additionally, in an effort to provide aconcise description of these embodiments, all features of an actualimplementation may not be described in the specification. It should beappreciated that in the development of any such actual implementation,as in any engineering or design project, numerousimplementation-specific decisions must be made to achieve thedevelopers' specific goals, such as compliance with system-related andbusiness-related constraints, which may vary from one implementation toanother. Moreover, it should be appreciated that such a developmenteffort might be complex and time consuming, but would nevertheless be aroutine undertaking of design, fabrication, and manufacture for those ofordinary skill having the benefit of this disclosure.

When introducing elements of various embodiments of the presentdisclosure, the articles “a,” “an,” and “the” are intended to mean thatthere are one or more of the elements. The terms “comprising,”“including,” and “having” are intended to be inclusive and mean thatthere may be additional elements other than the listed elements.Additionally, it should be understood that references to “oneembodiment” or “an embodiment” of the present disclosure are notintended to be interpreted as excluding the existence of additionalembodiments that also incorporate the recited features.

Embodiments of the present disclosure generally relate to techniques ofperforming precise indoor localization and tracking of one or morewireless electronic devices (e.g., within an indoor environment orotherwise within a range of 1-10 meters). In certain embodiments, thepresent embodiments may include a precise indoor localization algorithm(PILA) that may be executed by one or more processors of an electronicdevice to generate a radio frequency (RF) map of a number of wirelesselectronic devices (e.g., which may be referred to herein as “nodes” ofthe RF map) within an indoor environment to determine the precisephysical location (e.g., XY-coordinates or longitudinal and latitudinalcoordinates generally within less than +−x meters of their actuallocation) of the wireless electronic devices within an indoorenvironment. Indeed, in some embodiments, the RF map may be generatedbased on range and angle of arrival (AoA) matrices calculated withrespect to each of the number of wireless electronic devices from theperspective of the electronic device executing the PILA and with respectto each other of the number of wireless electronic devices.

In accordance with the present embodiments, based on the calculatedrange and AoA matrices and/or the calculated distance measurements basedon acceleration, the one or more processors of the electronic device mayiteratively adjust the RF map by reshaping and/or rotating the RF map(e.g., based on multi-dimensional scaling [MDS] and field of view [FOV])to reduce and/or eliminate “front-back” ambiguity, “flip-node”ambiguity, out-of-bounds nodes, and so forth as the number of wirelesselectronic devices remain stationary and/or move with respect to eachother electronic device within the indoor environment. In this way, thepresent embodiments may provide techniques to efficiently track andpinpoint the precise physical location of wireless electronic deviceswithin indoor environments, or otherwise in any of various environmentsin which large-scale satellite systems such as, GPS, may be inaccurateand/or inefficient (e.g., within a distance range of 1-10 meters).

With the foregoing in mind, a general description of suitable electronicdevices that may be useful in performing precise indoor localization andtracking of electronic devices will be provided below. Turning first toFIG. 1, an electronic device 10 according to an embodiment of thepresent disclosure may include, among other things, one or moreprocessor(s) 12, memory 14, nonvolatile storage 16, a display 18, inputstructures 22, an input/output (I/O) interface 24, network interfaces26, one or more transceivers 28, and a power source 29. The variousfunctional blocks shown in FIG. 1 may include hardware elements(including circuitry), software elements (including computer code storedon a computer-readable medium) or a combination of both hardware andsoftware elements. It should be noted that FIG. 1 is merely one exampleof a particular implementation and is intended to illustrate the typesof components that may be present in the electronic device 10.

By way of example, the electronic device 10 represented by the blockdiagram of FIG. 1 may be the notebook computer depicted in FIG. 2, thehandheld device depicted in FIG. 3, the handheld device depicted in FIG.4, the desktop computer depicted in FIG. 5, the wearable electronicdevice depicted in FIG. 6, or similar devices. It should be noted thatthe processor(s) 12 and/or other data processing circuitry of FIG. 1 maybe generally referred to herein as “data processing circuitry.” Suchdata processing circuitry may be embodied wholly or in part as software,firmware, hardware, or any combination thereof. Furthermore, the dataprocessing circuitry may be a single contained processing module or maybe incorporated wholly or partially within any of the other elementswithin the electronic device 10.

In the electronic device 10 of FIG. 1, the processor(s) 12 and/or otherdata processing circuitry may be operably coupled with the memory 14 andthe nonvolatile storage 16 to perform various algorithms. Such programsor instructions executed by the processor(s) 12 may be stored in anysuitable article of manufacture that includes one or more tangible,computer-readable media at least collectively storing the instructionsor routines, such as the memory 14 and the nonvolatile storage 16. Thememory 14 and the nonvolatile storage 16 may include any suitablearticles of manufacture for storing data and executable instructions,such as random-access memory, read-only memory, rewritable flash memory,hard drives, and optical discs. Also, programs (e.g., an operatingsystem) encoded on such a computer program product may also includeinstructions that may be executed by the processor(s) 12 to enable theelectronic device 10 to provide various functionalities.

In certain embodiments, the display 18 may be a liquid crystal display(LCD), which may allow users to view images generated on the electronicdevice 10. In some embodiments, the display 18 may include a touchscreen, which may allow users to interact with a user interface of theelectronic device 10. Furthermore, it should be appreciated that, insome embodiments, the display 18 may include one or more organic lightemitting diode (OLED) displays, or some combination of LCD panels andOLED panels.

The input structures 22 of the electronic device 10 may enable a user tointeract with the electronic device 10 (e.g., pressing a button toincrease or decrease a volume level). The I/O interface 24 may enableelectronic device 10 to interface with various other electronic devices,as may the network interface 26. The network interface 26 may include,for example, interfaces for a personal area network (PAN), such as aBluetooth network, for a local area network (LAN) or wireless local areanetwork (WLAN), such as an 802.11x Wi-Fi network, and/or for a wide areanetwork (WAN), such as a 3rd generation (3G) cellular network, 4thgeneration (4G) cellular network, long term evolution (LTE) cellularnetwork, or long term evolution license assisted access (LTE-LAA)cellular network. The network interface 26 may also include interfacesfor, for example, broadband fixed wireless access networks (WiMAX),mobile broadband Wireless networks (mobile WiMAX), asynchronous digitalsubscriber lines (e.g., ADSL, VDSL), digital videobroadcasting-terrestrial (DVB-T) and its extension DVB Handheld (DVB-H),ultra-Wideband (UWB), alternating current (AC) power lines, and soforth.

In certain embodiments, to allow the electronic device 10 to communicateover the aforementioned wireless networks (e.g., Wi-Fi, WiMAX, mobileWiMAX, 4G, LTE, and so forth), the electronic device 10 may include atransceiver 28. The transceiver 28 may include any circuitry the may beuseful in both wirelessly receiving and wirelessly transmitting signals(e.g., data signals). Indeed, in some embodiments, as will be furtherappreciated, the transceiver 28 may include a transmitter and a receivercombined into a single unit, or, in other embodiments, the transceiver28 may include a transmitter separate from the receiver. For example,the transceiver 28 may transmit and receive OFDM signals (e.g., OFDMdata symbols) to support data communication in wireless applicationssuch as, for example, PAN networks (e.g., Bluetooth), WLAN networks(e.g., 802.11x Wi-Fi), WAN networks (e.g., 3G, 4G, and LTE and LTE-LAAcellular networks), WiMAX networks, mobile WiMAX networks, ADSL and VDSLnetworks, DVB-T and DVB-H networks, UWB networks, and so forth. Asfurther illustrated, the electronic device 10 may include a power source29. The power source 29 may include any suitable source of power, suchas a rechargeable lithium polymer (Li-poly) battery and/or analternating current (AC) power converter.

In certain embodiments, the electronic device 10 may take the form of acomputer, a portable electronic device, a wearable electronic device, orother type of electronic device. Such computers may include computersthat are generally portable (such as laptop, notebook, and tabletcomputers) as well as computers that are generally used in one place(such as conventional desktop computers, workstations and/or servers).In certain embodiments, the electronic device 10 in the form of acomputer may be a model of a MacBook®, MacBook® Pro, MacBook Air®,iMac®, Mac® mini, or Mac Pro® available from Apple Inc. By way ofexample, the electronic device 10, taking the form of a notebookcomputer 10A, is illustrated in FIG. 2 in accordance with one embodimentof the present disclosure. The depicted computer 10A may include ahousing or enclosure 36, a display 18, input structures 22, and ports ofan IO interface 24. In one embodiment, the input structures 22 (such asa keyboard and/or touchpad) may be used to interact with the computer10A, such as to start, control, or operate a GUI or applications runningon computer 10A. For example, a keyboard and/or touchpad may allow auser to navigate a user interface or application interface displayed ondisplay 18.

FIG. 3 depicts a front view of a handheld device 10B, which representsone embodiment of the electronic device 10. The handheld device 10B mayrepresent, for example, a portable phone, a media player, a personaldata organizer, a handheld game platform, or any combination of suchdevices. By way of example, the handheld device 10B may be a model of aniPod® or iPhone® available from Apple Inc. of Cupertino, Calif. Thehandheld device 10B may include an enclosure 36 to protect interiorcomponents from physical damage and to shield them from electromagneticinterference. The enclosure 36 may surround the display 18. The I/Ointerfaces 24 may open through the enclosure 36 and may include, forexample, an i/O port for a hard wired connection for charging and/orcontent manipulation using a standard connector and protocol, such asthe Lightning connector provided by Apple Inc., a universal service bus(USB), or other connector and protocol.

User input structures 22, in combination with the display 18, may allowa user to control the handheld device 10B. For example, the inputstructures 22 may activate or deactivate the handheld device 10B,navigate user interface to a home screen, a user-configurableapplication screen, and/or activate a voice-recognition feature of thehandheld device 10B. Other input structures 22 may provide volumecontrol, or may toggle between vibrate and ring modes. The inputstructures 22 may also include a microphone may obtain a user's voicefor various voice-related features, and a speaker may enable audioplayback and/or certain phone capabilities. The input structures 22 mayalso include a headphone input may provide a connection to externalspeakers and/or headphones.

FIG. 4 depicts a front view of another handheld device 10C, whichrepresents another embodiment of the electronic device 10. The handhelddevice OC may represent, for example, a tablet computer, or one ofvarious portable computing devices. By way of example, the handhelddevice 10C may be a tablet-sized embodiment of the electronic device 10,which may be, for example, a model of an iPad® available from Apple Inc.of Cupertino, Calif.

Turning to FIG. 5, a computer 10D may represent another embodiment ofthe electronic device 10 of FIG. 1. The computer 10D may be anycomputer, such as a desktop computer, a server, or a notebook computer,but may also be a standalone media player or video gaming machine. Byway of example, the computer 10D may be an iMac®, a MacBook, or othersimilar device by Apple Inc. It should be noted that the computer 10Dmay also represent a personal computer (PC) by another manufacturer. Asimilar enclosure 36 may be provided to protect and enclose internalcomponents of the computer 10D such as the display 18. In certainembodiments, a user of the computer 10D may interact with the computer10D using various peripheral input devices, such as the keyboard 22A ormouse 22B (e.g., input structures 22), which may connect to the computer10D.

Similarly, FIG. 6 depicts a wearable electronic device 10E representinganother embodiment of the electronic device 10 of FIG. 1 that may beconfigured to operate using the techniques described herein. By way ofexample, the wearable electronic device 10E, which may include awristband 43, may be an Apple Watch® by Apple, Inc. However, in otherembodiments, the wearable electronic device 10E may include any wearableelectronic device such as, for example, a wearable exercise monitoringdevice (e.g., pedometer, accelerometer, heart rate monitor), or otherdevice by another manufacturer. The display 18 of the wearableelectronic device 10E may include a touch screen display 18 (e.g., LCD,OLED display, active-matrix organic light emitting diode (AMOLED)display, and so forth), as well as input structures 22, which may allowusers to interact with a user interface of the wearable electronicdevice 10E.

With the foregoing in mind, FIG. 7 depicts a schematic diagram of thetransceiver 28. As illustrated, the transceiver 28 may include atransmitter 44 (e.g., transmitter path) and a receiver 46 (e.g.,receiver path) coupled as part of a single unit. As depicted, thetransmitter 44 may receive a signal 45 that may be initially modulatedvia a coordinate rotation digital computer (CORDIC) 48 that may, in someembodiments, be used to process individual Cartesian represented datasymbols (e.g., OFDM symbols) into polar amplitude and phase components.In some embodiments, the CORDIC 48 may include a digital signalprocessor (DSP) or other processor architecture that may be used toprocess the incoming signal 45. In some embodiments, the CORDIC 48 mayalso communicate with a transceiver processor 50 (e.g., on-boardprocessor) that may be used to process transmitted and/or received WLAN(e.g., Wi-Fi) and/or cellular (e.g., LTE) signals.

In certain embodiments, during operation, the transmitter 44 may receivea Cartesian coordinate represented signal 45, which may include, forexample, data symbols encoded according to orthogonal I/Q vectors. Thus,when an I/Q signal is converted into an electromagnetic wave (e.g.,radio frequency (RF) signal, microwave signal, millimeter wave signal),the conversion is generally linear as the I/Q may be frequencyband-limited. The I/Q signals 45 may be then respectively passed to highpass filters (HPFs) 51 and 52, which may be provided to pass the highfrequency components of the I/Q signals 45 and filter out the lowfrequency components. As further illustrated, the I/Q signals 45 may bethen respectively passed to mixers 54 and 56, which may be used to mix(e.g., multiply or upconvert) the in-phase (I) component and thequadrature (Q) component of the I/Q signals 45.

In certain embodiments, as further illustrated in FIG. 7, a transmitterphase lock loop (PLL-TX) or oscillator 58 may be provided to generate900 out of phase oscillation signals by which to mix the orthogonalin-phase (I) component and the quadrature (Q) component to generate acarrier frequency and/or radio frequency (RF) signal. The in-phase (I)component and the quadrature (Q) component signals may be thenrecombined via a summer 62, and then passed to a power amplifier (PA) 64to amplify the summed signal, and to generate an electromagnetic signal(e.g., RF signal, microwave signal, millimeter wave signal) to beprovided to antennas 66 and 68 (e.g., multiple input multiple output[MIMO] antennas) for transmission.

In some embodiments, the antennas 66 and 68 may include orthogonal UWBantennas, or any other of various antennas that may be useful insupporting increased field-of-view (FOV) coverage and efficient angle ofarrival (AoA) detection. However, as will be further appreciated,because the transceiver 28 may include two antennas 66 and 68, thetransceiver 28 may, in some embodiments, be susceptible to “front-back”ambiguity. In some embodiments, the antennas 66 and 68 may be includedon the same integrated chip as the transceiver 28 architecture. However,in other embodiments, the antennas 66 and 68 may be fabricated as partof a separate chip and/or circuitry that may be coupled to the othercircuitry components (e.g., PA 64) of the transceiver 28.

In certain embodiments, as previously noted, the transmitter 44 may becoupled together with the receiver 46. Thus, as illustrated, thetransceiver 28 may further include a transmitter/receiver (T/R) switch69 or other circulator device, which may be useful in routing signalsfrom the transmitter 44 to the antennas 66 and 68 and routing signalsreceived via the antennas 66 and 68 to the receiver 46 (e.g., receiverpath of the transceiver 28). In certain embodiments, the T/R switch 69may be coupled to RF front end circuitry 70, which may include one ormore RF filters and similar circuitry used for filtering andpre-processing received and/or transmitted RF signals.

As further depicted in FIG. 7, during operation, the receiver 46 mayreceive RF signals (e.g., LTE and/or Wi-Fi signals) detected by theantennas 66 and 68. For example, as illustrated in FIG. 7, receivedsignals may be received by the receiver 46. The received signals may bethen passed to a mixer 71 (e.g., downconverter) to mix (e.g., multiply)the received signals with an IF signal (e.g., 10-20 megahertz (MHz)signal) provided by a receiver phase lock loop (PLL-RX) or oscillator72.

In certain embodiments, as further illustrated in FIG. 7, the IF signalmay be then passed to a low-pass filter 73, and then mixer 76 that maybe used to mix (e.g., downconvert a second time) with a lower IF signalgenerated by an oscillator 78 (e.g., numerically controlled oscillator).The oscillator 78 may include any device that may be useful ingenerating an analog or discrete-time and/or frequency domain (e.g.,digital domain) representation of a carrier frequency signal. The IFsignal may be then passed to the transceiver processor 50 to be furtherprocessed and analyzed.

In certain embodiments, the electronic device 10 may be used to performindoor localization and tracking. Indeed, certain IPS systems such as,“fingerprinting” may include a technique of developing a radio frequency(RF) map (e.g., radio map) of particular areas of a location orenvironment based on predetermined received signal strength indicators(RSSI) values emanating, for example, from a Wi-Fi connected device orother wireless connectivity “hotspots.” However, “fingerprinting”systems most often include an offline calibration or training phase inwhich RSSI values must be collected for hundreds if not thousands ofWi-Fi connected devices or other wireless connectivity “hotspots” toachieve even marginal localization accuracy.

Furthermore, certain real-time environmental conditions such as, forexample, obstructions due to the presence of pedestrians, the openingand closing of doors, as well as variations in atmospheric conditions(e.g., humidity, temperature) may degrade RF signals and affect the RSSIvalues. Moreover, the transceivers employed in many mobile and wearableelectronic devices, as well as those in in-home electronic devices, maybe subject to “front-back” ambiguity, or ambiguity with respect to aparticular wireless electronic device determining whether a signalarrives at that particular wireless electronic device from the front orfrom the back of that particular wireless electronic device.Accordingly, in certain embodiments, as will be further appreciated withrespect to FIGS. 8-22, it may be useful to provide techniques to performprecise indoor localization and tracking of one or more wirelesselectronic devices. It should be appreciated that, in certainembodiments, the present techniques (e.g., precise indoor localizationalgorithm [PILA]) may be performed by the processor(s) 12, thetransceiver processor 50, or in conjunction between the processor(s) 12and the transceiver 28.

Turning now to FIG. 8, an example diagram of an RF map 80 (e.g., radiomap) is illustrated. As depicted, the RF map 80 may include a number ofnodes 82 (e.g., “Node 1”), 84 (e.g., “Node 2”), 86 (e.g., “Node 3”), 88(e.g., “Node 4”), 90 (e.g., “Node 5”), and 92 (e.g., “Reference Node”).In certain embodiments, each of the nodes 82 (e.g., “Node 1”), 84 (e.g.,“Node 2”), 86 (e.g., “Node 3”), 88 (e.g., “Node 4”), 90 (e.g., “Node 5”)may represent any of various wireless electronic devices (e.g., mobilewireless electronic devices, in-home wireless devices, wearable wirelesselectronic devices, and so forth) that may be placed or situated withinan indoor environment (e.g., inside of residential, commercial, orindustrial buildings).

In one embodiment, each of the nodes 82 (e.g., “Node 1”), 84 (e.g.,“Node 2”), 86 (e.g., “Node 3”), 88 (e.g., “Node 4”), 90 (e.g., “Node 5”)may be connected to a WLAN (e.g., Wi-Fi, UWB, White-Fi, etc.) within theindoor environment (e.g., inside of residential, commercial, orindustrial buildings), and may each include at least two antennas (e.g.,similar to antennas 66 and 68 of the electronic device 10). Similarly,the node 92 (e.g., “Reference Node”) may represent, for example, theelectronic device 10 that may be used to generate one or more RF maps(e.g., radio maps) as part of the precise indoor localization andtracking techniques (e.g., indoor localization and tracking of nodes 82,84, 86, 88, and 90) described herein.

The RF map 80 may illustrate an example layout of the nodes 1, 2, 3, 4,and 5. For example, the RF map 80 may illustrate the respectivelocations of the nodes 1, 2, 3, 4, and 5 corresponding to wirelesselectronic devices within an indoor environment. As previously noted,“front-back” ambiguity may disparage the ability of the node 92 (e.g.,“Reference Node” or electronic device 10) to accurately resolve theactual location of the individuals nodes 1, 2, 3, 4, and 5.

For example, FIG. 9 illustrates an RF map 94 that depicts an example“front-back” ambiguity, as compared to the RF map 80 of FIG. 8. Asdepicted in FIG. 9, without the present techniques to be discussedherein, the node 92 (e.g., “Reference Node” or electronic device 10) mayresolve the nodes 1, 2, 3, 4, and 5 as being positioned at an inaccurateplace. For example, as depicted in the RF map 94 of FIG. 9, the node 1and the node 2 are resolved as being significantly closer to each other(e.g., as compared to the node 1 and the node 2 of the RF map 80 of FIG.8).

Similarly, the node 4 of the RF map 94 may be resolved as being locatedin a frontward position with respect to the node 92 (“Reference Node”)as shown in FIG. 9, as opposed to the actual backside location withrespect to the reference node as shown in FIG. 8. Specifically, theresolved location of the node 4 in the RF map 94 of FIG. 9 mayillustrate an example of “front-back” ambiguity. As further depicted inthe RF map 94 of FIG. 9, the node 5 may be resolved as being located onthe left side of the reference node as shown in FIG. 9, as opposed toactually being on the right side of the reference node as shown in FIG.8. The resolved location of the reference node in the RF map 94 of FIG.9 may illustrate an example of “flip-node” ambiguity.

In certain embodiments, as illustrated in FIG. 10, the processor(s) 12and/or the transceiver processor 50 of the electronic device 10 mayexecute a process 96 useful in correcting “front-back” ambiguity as partof the precise indoor localization and tracking techniques discussedherein. In certain embodiments, the process 96 may be a part of aprecise indoor localization algorithm (PILA) that may be stored in thememory 14 of the electronic device 10, and executed, for example, by theprocessor(s) 12 and/or the transceiver processor 50 of the electronicdevice 10. That is, the process 96 may include code or instructionsstored in a non-transitory machine-readable medium (e.g., the memory 14)and executed, for example, by the processor(s) 12 and/or the transceiverprocessor 50 of the electronic device 10.

In certain embodiments, the process 96 may begin with the processor(s)12 and/or the transceiver processor 50 calculating range R and AoA θmatrices with respect to each of the other nodes 1, 2, 3, 4, and 5(block 98). For example, in one embodiment, the processor(s) 12 and/orthe transceiver processor 50 may calculate a range R matrix that may beexpressed as:

$\begin{bmatrix}R_{00} & R_{10} & R_{20} & R_{30} & \ldots & \ldots \\R_{01} & R_{11} & R_{21} & R_{31} & \ldots & \ldots \\R_{02} & R_{12} & R_{22} & R_{32} & \ldots & \ldots \\R_{03} & R_{13} & R_{23} & R_{33} & \ldots & \ldots \\\vdots & \vdots & \vdots & \vdots & \vdots & \vdots \\\vdots & \vdots & \vdots & \vdots & \vdots & \vdots\end{bmatrix}$ Rxy = Ryxis the distance betweenXandYnodes

For example, R00 may represent the range value of the node 92(“Reference Node”) with respect to itself (e.g., as a reference), whileR01 may represent the range value between the node 92 (“Reference Node”)and the node 82 (e.g., “Node 1”), and so forth and so on. Similarly, theprocessor(s) 12 and/or the transceiver processor 50 may calculate a AoAθ matrix that may be expressed as:

$\begin{bmatrix}A_{00} & A_{10} & A_{20} & A_{30} & \ldots & \ldots \\A_{01} & A_{11} & A_{21} & A_{31} & \ldots & \ldots \\A_{02} & A_{12} & A_{22} & A_{32} & \ldots & \ldots \\A_{03} & A_{13} & A_{23} & A_{33} & \ldots & \ldots \\\vdots & \vdots & \vdots & \vdots & \vdots & \vdots \\\vdots & \vdots & \vdots & \vdots & \vdots & \vdots\end{bmatrix}$ A_(xy )  is the angle betweenXandYnodes measured fromy

For example, A00 may represent the AoA value of the node 92 (“ReferenceNode”) with respect to itself (e.g., as a reference), while A01 mayrepresent the AoA value between the reference node and the node 1, andso forth and so on. In certain embodiments, the processor(s) 12 and/orthe transceiver processor 50 may calculate the range and AoA matriceswith respect to each of the other nodes 1, 2, 3, 4, and 5 tospecifically correct and compensate for “front-back” ambiguity. Forexample, as will better appreciated with respect to the examplesillustrated in FIGS. 12 and 13, the process 96 may allow theprocessor(s) 12 and/or the transceiver processor 50 to correct andcompensate for “front-back” ambiguity based on, for example, a distanceand/or an acceleration measurement derived from the calculated range andAoA matrices. For example, in one embodiment, the processor(s) 12 and/orthe transceiver processor 50 may derive distance measurements from thecalculated range matrix based on, for example, the Friis powertransmission equation, which may be expressed as:

$P_{r} = {P_{t}\frac{G_{t}G_{r}\lambda_{0}^{2}}{\left( {4\pi\; R} \right)^{2}}}$

In equation (1), P_(r) may represent, for example, the power level ofthe signal received (e.g., at the electronic device 10), while P_(t) mayrepresent, for example, the power level of the signal transmitted by oneor more of the nodes 1, 2, 3, 4, and 5. Similarly, Gt may represent thegain of the signal received (e.g., at the electronic device 10), whileGr may represent, for example, the gain of the signal transmitted by oneor more of the nodes 1, 2, 3, 4, and 5. Lastly, the term 1 may representthe free space wavelength, while R is the range (e.g., corresponding tothe range values of the range matrix).

In certain embodiments, the process 96 may continue with theprocessor(s) 12 and/or the transceiver processor 50 filtering (block100) the range and AoA matrices (e.g., via one or more infinite impulseresponse [IIR] filters) calculated at block 98 to quantized the rangeand AoA matrices. The process 96 may continue with the processor(s) 12and/or the transceiver processor 50 generating (block 102) a set ofdistance points (e.g., XY coordinates) based on, for example, the rangeand AoA matrices calculated at block 98. For example, in certainembodiments, the processor(s) 12 and/or the transceiver processor 50 mayconvert polar coordinate distance values (e.g., represented in a3-dimensional (3D) form) derived from the calculated range and AoAmatrices into Cartesian coordinate values (e.g., represented in a2-dimensional (2D) form) for the purposes of precision and accuracy. Forexample, the x and y rectangular coordinate values may be expressed as:x=r cos θy=r sin θ

The process 96 may continue with the processor(s) 12 and/or thetransceiver processor 50 performing a long-term filtering algorithm togenerate a filtered distance coordinates matrix (e.g., X′, Y′) (block104) and filtered range and AoA matrix (e.g., R′, θ′) (block 106). Theprocess 96 may then continue with the processor(s) 12 and/or thetransceiver processor 50 utilizing the range matrix R and the filteredrange matrix R′ (block 108) to accurately resolve the nodes 1, 2, 3, 4,and 5 as being from the backside of the reference node (e.g., “ReferenceNode” or electronic device 10). For example, in certain embodiments, theprocessor(s) 12 and/or the transceiver processor 50 may compare therange matrix R and the filtered range matrix R′, and if the range matrixR and the filtered range matrix R′ are determined to be very different,then one or more of the nodes 1, 2, 3, 4, and 5 may be determined asbeing on the backside of the reference node.

Specifically, in some embodiments, the processor(s) 12 and/or thetransceiver processor 50 may compare the range matrix R and the filteredrange matrix R′ based on, for example, the following expressions:(θ mod)_(i)=−θ for i, where S _(i)>median*1.5Σ₀ ^(N)(R′−R)² >>S=[S ₀ ,S ₁ ,S ₂ ,S ₃ , . . . S _(N−1) ,S _(N)]

As generally delineated by the above expressions, the range matrix R andthe filtered range matrix R′ are very different when Si is greater thanor much greater than the median (S) times 1.5, where S is a particularnode and i is a node index. Thus, when the above expressions aresatisfied, the processor(s) 12 and/or the transceiver processor 50 maydetermine that one or more of the nodes 1, 2, 3, 4, and 5 are on thebackside of the reference node. As further illustrated by the aboveexpressions, the AoA of the one or more of the nodes 1, 2, 3, 4, and 5resolved as being on the backside of the reference node may be negated.

In certain embodiments, the process 96 may continue with theprocessor(s) 12 and/or the transceiver processor 50 applying (block 110)field of view (FOV) filter based on the aforementioned expressionsdiscussed with respect to block 108. For example, applying the FOVfilter may be part of a sub-process to determine which of the one ormore of the nodes 1, 2, 3, 4, and 5 are on the backside of the referencenode to “flip” or correct for “flip-node” ambiguity. The process 96 maycontinue with the processor(s) 12 and/or the transceiver processor 50generating a filtered distance coordinates matrix (e.g., Xg, Yg) (block112) and filtered range and AoA matrix (e.g., Rg, θg) (block 114). Theprocess 96 may continue with the processor(s) 12 and/or the transceiverprocessor 50 performing (block 116) a multidimensional scaling (MDS)algorithm to generate the corrected shape (e.g., corrected for“front-back” ambiguity and “flip-node” ambiguity) RF map of the nodes 1,2, 3, 4, and 5 are on the backside of the reference node.

In certain embodiments, the process 96 may continue with theprocessor(s) 12 and/or the transceiver processor 50 generating (block118) distance coordinate matrices (e.g., Xm, Yin) based on, for example,the MDS algorithm generated at block 116, in which {\textstyle E_{m}} Xmis the x-coordinate matrix of {\textstyle m}m eigenvectors and{\textstyle \lambda_{m}}Ym is the y-coordinate matrix of {\textstyle m}meigenvectors. The process 96 may then conclude with the processor(s) 12and/or the transceiver processor 50 generating (block 120) distancecoordinate matrices (e.g., Xr, Yr) based on distance coordinate matrices(e.g., Xm, Ym) (block 118), in which {\textstyle E_{m)}}Xr is thex-coordinate matrix of {\textstyle m}r real values and {\textstyle\Lambda_{m}}Yr is the y-coordinate matrix of {\textstyle m}r realvalues. {\textstyle B}

Turning now to FIG. 11, a process 122 is illustrated that is useful inidentifying “flipped” nodes as part of the precise indoor localizationand tracking techniques discussed herein. It should be appreciated that,in some embodiments, the process 122 may be performed in conjunction,concurrently, or otherwise as part of a sub-process with respect to theprocess 96 discussed above in FIG. 10. Indeed, in certain embodiments,the process 122 may be a part of a precise indoor localization algorithm(PILA) that may be stored in the memory 14 of the electronic device 10,and executed, for example, by the processor(s) 12 and/or the transceiverprocessor 50 of the electronic device 10. For example, as illustrated bythe process 122 in FIG. 11, the process 122 may begin with theprocessor(s) 12 and/or the transceiver processor 50 utilizing thecalculated distance coordinate matrices (e.g., X, Y) (block 124), thecalculated range and AoA matrices (e.g., R, θ) (block 126), thegenerated filtered distance coordinate matrices (e.g., X′, Y′) (block128), and the generated filtered range and AoA matrices (e.g., R′, θ′)(block 130) to identify which of the nodes 1, 2, 3, 4, and 5 areresolved as being “flipped” with respect to their actual location.

In certain embodiments, the process 122 may continue with theprocessor(s) 12 and/or the transceiver processor 50 calculating (block132) a difference between the range matrix R and the filtered rangematrix R′. The process 122 may continue with the processor(s) 12 and/orthe transceiver processor 50 calculating (block 134) maximum deviationnode based on the difference between the range matrix R and the filteredrange matrix R′ calculated at block 132. For example, the node of theone or more nodes 1, 2, 3, 4, and 5 may indicate that that particularnode is being resolved as “flipped.” The process 122 may then concludewith the processor(s) 12 and/or the transceiver processor 50 negating(block 134) the AoA of the maximum deviation node, and identify themaximum deviation node as being a “flipped” node.

FIG. 12 illustrates an RF map example of the aforementioned techniquesof correcting “front-back” ambiguity and “flip-node” ambiguity describedwith respect to FIGS. 10 and 11. As depicted by the RF map 138illustrated in FIG. 12, the processor(s) 12 and/or the transceiverprocessor 50 may detect and calculate the location of the nodes 1, 2,and 4 as part of the calculated range and AoA matrices (e.g., R, θ) andcalculate the node 140 (e.g., “Node 4”) as part of the generatedfiltered range and AoA matrices (e.g., R′, θ′). Based on the calculatedrange and AoA matrices (e.g., R, θ) and generated filtered range and AoAmatrices (e.g., R′, θ′), the processor(s) 12 and/or the transceiverprocessor 50 may determine that that the distance R24 is not equal tothe distance R24′, and that the distance R14 is not equal to thedistance R14′. Thus, the processor(s) 12 and/or the transceiverprocessor 50 may determine that the node 4 is a “flipped” node, andresolve the actual location of the node 4 as being at the location ofthe node 4.

FIGS. 13 and 14 illustrate examples of the aforementioned techniques ofcorrecting “front-back” ambiguity and “flip-node” ambiguity describedwith respect to FIGS. 10 and 11 based on, for example, an accelerationcalculation. As depicted by FIG. 13, the reference node may bepositioned in a 3-dimensional (3-D) space (e.g., XYZ space) and theaccelerometers, magnetometers, gyroscopes, and so forth of theelectronic device 10 may be used to generate real value distancecoordinate matrices (e.g., Xr, Yr), and, by extension, identify“front-back” and “flip-node” ambiguities.

For example, as illustrated by the table 144 in FIG. 14, theprocessor(s) 12 and/or the transceiver processor 50 may determine thatas the distance from the reference node to one or more of the nodes 1,2, 3, 4, and 5 increases in a positive direction with respect to thecalculated acceleration vectors, the one or more nodes 1, 2, 3, 4, and 5may represent a “flipped” node. As further depicted by the table 144,for all other cases, the processor(s) 12 and/or the transceiverprocessor 50 may determine that the one or more nodes 1, 2, 3, 4, and 5have not been resolved as being “flipped”.

FIGS. 15-18 illustrate additional RF map examples of the aforementionedtechniques of correcting “front-back” ambiguity and “flip-node”ambiguity described with respect to FIGS. 10 and 11, and morespecifically, illustrations of how the previously discussed MDSalgorithm is used to construct an RF map adjusted and corrected for“front-back” ambiguity and/or “flip-node” ambiguity. For example, FIG.15 illustrates an RF map 146 of an example layout (e.g., the actualphysical arrangement and respective locations) of nodes 1, 2, and 5 thatmay be placed or situated within an indoor environment (e.g., inside ofresidential, commercial, or industrial buildings) generated based on,for example, the calculated range and AoA matrices (e.g., R, θ) withrespective distances from the reference node. FIG. 16 illustrates an RFmap 148 generated after the aforementioned MDS algorithm is applied, andthus the shape of the RF map 148 is constructed to generate fourpossible shapes of the RF map 148 corresponding to the actualarrangement of the nodes 1, 2, and 5.

In certain embodiments, the processor(s) 12 and/or the transceiverprocessor 50 may determine which of the four possible shapes of the RFmap 148 to select and rotate to match (or to best match) the actualarrangement of the nodes 1, 2, and 5, as illustrated by the RF map 148of FIG. 15. For example, as illustrated by the RF map 150 of FIG. 17,the processor(s) 12 and/or the transceiver processor 50 may determinethe precise rotation (or the best possible rotation) of the selectedshape of the four possible shapes of, for example, the RF map 148 ofFIG. 16. Specifically, the processor(s) 12 and/or the transceiverprocessor 50 may determine the precise rotation (or the best possiblerotation) of the selected shape based on, for example, the calculatedAoA matrix (e.g., 0).

For example, as illustrated by the RF map 152 of FIG. 18, after the MDSalgorithm is applied and the shape of the RF map 150 is rotated by anangle rot, the resulting shape (e.g., semi-parallelogram shape asillustrated) of the RF map 150 of FIG. 17 is the RF map 152 of FIG. 18.As it may be appreciated, the RF map 152 of FIG. 18 corresponds to theactual arrangement of the nodes 1, 2, and 4 as first illustrated withrespect to FIG. 15. In this way, the processor(s) 12 and/or thetransceiver processor 50 may determine the actual location of the nodes1, 2, and 5 by correcting and adjusting for “front-back” ambiguity and“flip-node” ambiguity.

Turning now to FIG. 19, which illustrates a process 154 useful indetermining stationary versus moving nodes as part of the precise indoorlocalization and tracking techniques discussed herein. The process 154may be a part of a precise indoor localization algorithm (PILA) that maybe stored in the memory 14 of the electronic device 10, and executed,for example, by the processor(s) 12 and/or the transceiver processor 50of the electronic device 10. In certain embodiments, the process 154 mayinclude a stationary filtering process to identify stationary versusmoving nodes 1, 2, 3, 4, and 5.

As illustrated by the process 154 in FIG. 19, the process 154 may beginwith the processor(s) 12 and/or the transceiver processor 50 utilizing(block 156) the calculated distance coordinate matrices (e.g., Xr, Yr)(e.g., previously calculated as part of the process 122 of FIG. 11) totune the {\textstyle E_{m}}Xr matrix of {\textstyle m}r realx-coordinates values and {\textstyle \Lambda_{m}}Yr matrix of{\textstyle m}r real y-coordinates values and generate stationary boundspreX, preY (block 158) for each of the nodes 1, 2, 3, 4, and 5.

For example, in certain embodiments, the processor(s) 12 and/or thetransceiver processor 50 may generate stationary bounds that may beexpressed as:pre=cos t*pre+(1−cos t)N _(r), where 0.6≤cos t≤0.99

In certain embodiments, the processor(s) 12 and/or the transceiverprocessor 50 may generate XY stationary bounds for each of the nodes 1,2, 3, 4, and 5, such that if the processor(s) 12 and/or the transceiverprocessor 50 determines that any of the nodes 1, 2, 3, 4, and 5 does notmove outside of the stationary bounds preX, preY (e.g., for a period oftime), then the nodes 1, 2, 3, 4, and 5 may be determined as beingstationary. Indeed, in the above expression, pre may represent theoriginal location of one or more of the nodes 1, 2, 3, 4, and 5, whileNr may represent the new location (e.g., potentially having been moved adistance from the original location).

In certain embodiments, the process 154 may continue with theprocessor(s) 12 and/or the transceiver processor 50 looping (decision160) each of the nodes 82 (e.g., “Node 1”), 84 (e.g., “Node 2”), 86(e.g., “Node 3”), 88 (e.g., “Node 4”), 90 and (e.g., “Node 5”) throughthe stationary bounds preX, preY. As depicted by decision 160, theprocessor(s) 12 and/or the transceiver processor 50 may perform afor-loop function in which the processor(s) 12 and/or the transceiverprocessor 50 may loop through iterations until one or more of the nodes1, 2, 3, 4, and 5 are determined to be outside of the stationary boundspreX, preY.

In certain embodiments, once one or more of the nodes 1, 2, 3, 4, and 5is determined to be outside of the stationary bounds preX, preY, theprocess 154 may continue with the processor(s) 12 and/or the transceiverprocessor 50 adding (block 162) the angle of the one or more nodes tothe previously calculated AoA matrix (e.g., 0). The process 154 may thencontinue with the processor(s) 12 and/or the transceiver processor 50applying a long term average of the updated AoA matrix (e.g., 0) andgenerating an angle offset (block 164) based thereon. The process 154may then continue with the processor(s) 12 and/or the transceiverprocessor 50 rotating (block 166) the shape of the generated RF mapbased on the {\textstyle E_{m}}Xr matrix of {\textstyle m}r realx-coordinates values and {\textstyle \Lambda_{m}}Yr matrix of{\textstyle m}r real y-coordinates values (e.g., from block 156) and theangle offset generated at block 164. The process 154 may then concludewith the processor(s) 12 and/or the transceiver processor 50 generatingstationary distance coordinate matrices (e.g., Xs, Ys), and, byextension, identify which of the nodes 1, 2, 3, 4, and 5 are stationary.

As an example of the process 154 described with respect to FIG. 19, FIG.20 illustrates an RF map 170 of an example layout (e.g., the actualphysical arrangement and respective locations) of nodes 1, 2, and 5 thatmay be placed or situated within an indoor environment (e.g., inside ofresidential, commercial, or industrial buildings). FIG. 21 depicts aplot 172 illustrating an application of FOV filter, in which the arrows174 and 176 may, in one embodiment, represent the calculated stationarybounds preX and preY, respectively. The plot 172 illustrates that thenode 178 (e.g., “X1” corresponding to the node 82 in FIG. 20) and thenode 180 (e.g., “X2” corresponding to the node 84 in FIG. 20) are eachwithin the bounds indicated by the arrows 174 and 176.

On the other hand, the node 182 (e.g., “X5” corresponding to the node 90in FIG. 20) may be detected as being outside of the bounds indicated bythe arrows 174 and 176. In such a case, the AoA of the node 182 may notbe “trusted” as being accurate, and thus the processor(s) 12 and/or thetransceiver processor 50 may correct for movement of the node 182utilizing the MDS algorithm and the illustrated yaw calculations tocorrect for AoA variations.

Turning now to FIG. 22, a flow diagram is presented, illustrating anembodiment of a process 184 useful in performing precise indoorlocalization and tracking of various electronic devices. It should beappreciated that, in some embodiments, the process 184 may, at least insome embodiments, include an aggregation of the process 98, the process122, and the process 154 previously discussed with respect to FIGS. 10,11 and 19. In certain embodiments, the process 184 may include a preciseindoor localization algorithm (PILA) that may be stored in the memory 14of the electronic device 10, and executed, for example, by theprocessor(s) 12 and/or the transceiver processor 50 of the electronicdevice 10.

In certain embodiments, the process 184 may begin with the processor(s)12 and/or the transceiver processor 50 performing (block 186) front-backnode detection. The process 184 may then continue with the processor(s)12 and/or the transceiver processor 50 performing (block 188) stationarynode detection. The process 184 may then continue with the processor(s)12 and/or the transceiver processor 50 performing (block 190) angle ofarrival (AoA) error correction. For example, if the yaw calculations ofthe nodes 1, 2, 3, 4, and 5 changes, for example, by +−20° (e.g.,indicating that one or more of the nodes 1, 2, 3, 4, and 5 have moved)the new AoA measurement is expected to change by 20 degrees +−20°. Ifsuch is not the case, longer term averages of the possible error can becomputed and applied to compensate for AoA errors when the nodes 1, 2,3, 4, and move positions.

The process 184 may then continue with the processor(s) 12 and/or thetransceiver processor 50 performing (block 192) angle offsetcalibration. The process 184 may then continue with the processor(s) 12and/or the transceiver processor 50 performing (block 194) field of view(FOV) filtering. For example, in some embodiments in which antenna phasemeasurements began to deteriorate (e.g., when the nodes are far right(+80°) or far left (−80°) outside the FOV bounds), yaw calculations maybe utilized to determine node angle, as the AoA may be inaccurate.

The process 184 may then continue with the processor(s) 12 and/or thetransceiver processor 50 performing (block 196) antenna phase differenceof arrival (PDOA) calibration. For example, in some embodiments, theantenna PDOA may be converted to AoA value to be initially input to thenode 92 (e.g., “Reference Node” or electronic device 10). The process184 may then conclude with the processor(s) 12 and/or the transceiverprocessor 50 performing (block 198) precise indoor localization andtracking of various wireless electronic devices.

The specific embodiments described above have been shown by way ofexample, and it should be understood that these embodiments may besusceptible to various modifications and alternative forms. It should befurther understood that the claims are not intended to be limited to theparticular forms disclosed, but rather to cover all modifications,equivalents, and alternatives falling within the spirit and scope ofthis disclosure.

The techniques presented and claimed herein are referenced and appliedto material objects and concrete examples of a practical nature thatdemonstrably improve the present technical field and, as such, are notabstract, intangible or purely theoretical. Further, if any claimsappended to the end of this specification contain one or more elementsdesignated as “means for [perform]ing [a function] . . . ” or “step for[perform]ing [a function] . . . ”, it is intended that such elements areto be interpreted under 35 U.S.C. 112(f). However, for any claimscontaining elements designated in any other manner, it is intended thatsuch elements are not to be interpreted under 35 U.S.C. 112(f).

What is claimed is:
 1. An electronic device configured to perform aprecise indoor localization algorithm (PILA), comprising: one or moreprocessors configured to: generate a radio frequency (RF) map of aplurality of wireless electronic devices located and tracked within anindoor environment based at least in part on a calculated range matrixand a calculated angle of arrival (AoA) matrix, wherein the calculatedrange matrix comprises distance measurements based at least in part onpower level of one or more signals received by the electronic device,the power level of one or more signals transmitted from the plurality ofwireless electronic devices, gain of the one or more signals received bythe electronic device, gain of the one or more signals transmitted bythe plurality of wireless electronic devices, free space wavelength,range values, or a combination thereof; adjust the RF map of theplurality of wireless electronic devices to compensate for a pluralityof possible distortions with respect to a physical location of theplurality of wireless electronic devices within the indoor environment;and generate an indication of the physical location of the plurality ofwireless electronic devices within the indoor environment based at leastin part on the adjusted RF map.
 2. The electronic device of claim 1,wherein the calculated AoA matrix comprises AoA data of each of theplurality of wireless electronic devices with respect to the electronicdevice.
 3. The electronic device of claim 1, wherein the plurality ofpossible distortions comprise front-back ambiguity.
 4. The electronicdevice of claim 1, wherein the plurality of possible distortionscomprise flipped node ambiguity.
 5. The electronic device of claim 1,wherein the one or more processors are configured to adjust the RF mapof the plurality of wireless electronic devices based on a determinationof whether one or more of the plurality of wireless electronic devicesare outside of bounds of a generated field of view (FOV) filter.
 6. Theelectronic device of claim 1, wherein the one or more processors areconfigured to adjust the RF map of the plurality of wireless electronicdevices by applying a multidimensional scaling (MDS) algorithm togenerate a corrected shape of the RF map based at least in part on thecalculated range matrix.
 7. The electronic device of claim 1, whereinthe one or more processors are configured to adjust the RF map of theplurality of wireless electronic devices by rotating a shape of the RFmap based at least in part on the calculated AoA matrix.
 8. A tangible,non-transitory, computer-readable medium having computer-executable codestored thereon, wherein the code comprises a precise indoor localizationalgorithm (PILA) including instructions that, when executed by one ormore processors of a computer, cause the computer to: locate and track aplurality of wireless electronic devices within an indoor environment;and cause an electronic device to generate and adjust a radio frequency(RF) map of the plurality of wireless electronic devices based at leastin part on a calculated range matrix and a calculated angle of arrival(AoA) matrix, wherein the RF map comprises an indication of a physicallocation of the plurality of wireless electronic devices within theindoor environment, and wherein the calculated range matrix comprisesdistance measurements based at least in part on power level of one ormore signals received by the electronic device, the power level of oneor more signals transmitted from the plurality of wireless electronicdevices, gain of the one or more signals received by the electronicdevice, gain of the one or more signals transmitted by the plurality ofwireless electronic devices, free space wavelength, range values, or acombination thereof.
 9. The non-transitory computer-readable medium ofclaim 8, wherein adjusting the RF map of the plurality of wirelesselectronic devices is to compensate for a plurality of possibledistortions with respect to the physical location of the plurality ofwireless electronic devices within the indoor environment.
 10. Thenon-transitory computer-readable medium of claim 9, wherein theplurality of possible distortions comprise flipped node ambiguity withrespect to the physical location of each of the plurality of wirelesselectronic devices.
 11. The non-transitory computer-readable medium ofclaim 10, wherein the flipped node ambiguity comprises adjusting the RFmap by moving at least one of the plurality of wireless electronicdevices from a left side location with respect to the electronic deviceon the RF map to a right side location with respect to the electronicdevice on the RF map.
 12. The non-transitory computer-readable medium ofclaim 9, wherein the plurality of possible distortions comprisesfront-back ambiguity with respect to the physical location of each ofthe plurality of wireless electronic devices.
 13. The non-transitorycomputer-readable medium of claim 12, wherein the front-back ambiguitycomprises adjusting the RF map by moving at least one of the pluralityof wireless electronic devices from a front side location with respectto the electronic device on the RF map to a backside location withrespect to the electronic device on the RF map.
 14. The non-transitorycomputer-readable medium of claim 8, wherein the code comprisesinstructions that, when executed by the one or more processors, causethe computer to: adjust the RF map by applying a multidimensionalscaling (MDS) algorithm to generate a corrected shape of the RF map; androtate the corrected shape of the RF map.
 15. The non-transitorycomputer-readable medium of claim 14, wherein the corrected shapecomprises reshaping the RF map to remove a front-back ambiguity, aflipped node ambiguity, or both.
 16. The non-transitorycomputer-readable medium of claim 8, wherein the calculated AoA matrixcomprises AoA data of each of the plurality of wireless electronicdevices with respect to the electronic device.
 17. A method, comprising:generating a radio frequency (RF) map of a plurality of wirelesselectronic devices located and tracked within an indoor environmentbased at least in part on a calculated range matrix and a calculatedangle of arrival (AoA) matrix with respect to an electronic device ofthe plurality of wireless electronic devices, wherein the calculatedrange matrix comprises distance measurements based at least in part onpower level of one or more signals received by the electronic device,the power level of one or more signals transmitted from the plurality ofwireless electronic devices, gain of the one or more signals received bythe electronic device, gain of the one or more signals transmitted bythe plurality of wireless electronic devices, free space wavelength,range values, or a combination thereof; adjusting the RF map of theplurality of wireless electronic devices to compensate for a pluralityof possible distortions with respect to a physical location of theplurality of wireless electronic devices within the indoor environment;and generating an indication of the physical location of the pluralityof wireless electronic devices within the indoor environment based atleast in part on the adjusted RF map.
 18. The method of claim 17,wherein the adjusting the RF map comprises correcting the plurality ofpossible distortions to accurately indicate actual positions of each ofthe plurality of wireless electronic devices with respect to theelectronic device, by reshaping the RF map, wherein the possibledistortions comprise front-back ambiguity, flipped node ambiguity, or acombination thereof.